scholarly journals Photometric constraint for absolute phase unwrapping from single-frequency fringe patterns

2021 ◽  
Author(s):  
zhao shuai qi ◽  
Xiaojun Liu ◽  
Zhao Wang ◽  
jiaqi yang ◽  
Yanning Zhang
Keyword(s):  
Phase Unwrapping ◽  
Single Frequency ◽  
Absolute Phase ◽  
Fringe Patterns

Practical Framework for Phase Retrieval and Invalidity Identification with Temporal Phase Unwrapping Method in Fringe Projection Profilometry

2011 ◽  
Vol 83 ◽  
pp. 179-184 ◽  
Author(s):  
Lei Huang ◽  
Anand Krishna Asundi
Keyword(s):  
Phase Retrieval ◽  
Phase Relationship ◽  
Phase Unwrapping ◽  
Three Dimensions ◽  
Fringe Projection ◽  
Temporal Phase ◽  
Absolute Phase ◽  
Fringe Patterns ◽  
Mean Square Errors ◽  
Fringe Projection Profilometry

Phase retrieval from fringe patterns is a primary procedure in fringe projection profilometry. Only accurate phase values result in three dimensions with certain accuracy. Phase shifting method plus temporal phase unwrapping approach provides not only the unwrapped absolute phase, but also the modulation map, background map, root mean square errors of least squares fitting, and phase relationship between two neighboring pixels, which can be used for the identification of phase invalidity. A practical phase retrieval frame work is presented to accurately calculate the absolute phase within reliable regions only, with which those unavailable phase points can be automatically identified with thresholds selection and criterion testing and then removed or interpolated according to applications. Experimental results show practical feasibility of the proposed framework.

Multi-view phase unwrapping with composite fringe patterns

2017 ◽  
Author(s):  
Tianyang Tao ◽  
Qian Chen ◽  
Yuzhen Zhang ◽  
Yan Hu ◽  
Jian Da ◽  
...  
Keyword(s):  
Phase Unwrapping ◽  
Fringe Patterns

scholarly journals Temporal phase unwrapping using deep learning

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Wei Yin ◽  
Qian Chen ◽  
Shijie Feng ◽  
Tianyang Tao ◽  
Lei Huang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
High Frequency ◽  
Phase Unwrapping ◽  
Motion Artifacts ◽  
Error Sources ◽  
Actual Measurement ◽  
Temporal Phase ◽  
Fringe Patterns ◽  
Frequency Phase

AbstractThe multi-frequency temporal phase unwrapping (MF-TPU) method, as a classical phase unwrapping algorithm for fringe projection techniques, has the ability to eliminate the phase ambiguities even while measuring spatially isolated scenes or the objects with discontinuous surfaces. For the simplest and most efficient case in MF-TPU, two groups of phase-shifting fringe patterns with different frequencies are used: the high-frequency one is applied for 3D reconstruction of the tested object and the unit-frequency one is used to assist phase unwrapping for the wrapped phase with high frequency. The final measurement precision or sensitivity is determined by the number of fringes used within the high-frequency pattern, under the precondition that its absolute phase can be successfully recovered without any fringe order errors. However, due to the non-negligible noises and other error sources in actual measurement, the frequency of the high-frequency fringes is generally restricted to about 16, resulting in limited measurement accuracy. On the other hand, using additional intermediate sets of fringe patterns can unwrap the phase with higher frequency, but at the expense of a prolonged pattern sequence. With recent developments and advancements of machine learning for computer vision and computational imaging, it can be demonstrated in this work that deep learning techniques can automatically realize TPU through supervised learning, as called deep learning-based temporal phase unwrapping (DL-TPU), which can substantially improve the unwrapping reliability compared with MF-TPU even under different types of error sources, e.g., intensity noise, low fringe modulation, projector nonlinearity, and motion artifacts. Furthermore, as far as we know, our method was demonstrated experimentally that the high-frequency phase with 64 periods can be directly and reliably unwrapped from one unit-frequency phase using DL-TPU. These results highlight that challenging issues in optical metrology can be potentially overcome through machine learning, opening new avenues to design powerful and extremely accurate high-speed 3D imaging systems ubiquitous in nowadays science, industry, and multimedia.

Multichannel interferometric SAR phase unwrapping using extended Kalman Smoother

2013 ◽  
Vol 5 (3) ◽  
pp. 429-436 ◽  
Author(s):  
Davide Chirico ◽  
Gilda Schirinzi
Keyword(s):  
Phase Unwrapping ◽  
Sensor Data ◽  
Bayesian Estimator ◽  
Bayesian Approaches ◽  
Strong Discontinuities ◽  
Absolute Phase ◽  
Multi Sensor Data Fusion ◽  
Digital Elevation ◽  
Elevation Model ◽  
Interferometric Sar

Phase unwrapping (PU) is one of the key processing steps in reconstructing the digital elevation model (DEM) of a scene from interferometric synthetic aperture radar (InSAR) data. The PU problem entails the estimation of an absolute phase from observation of its noisy principal (wrapped) values. Recently, PU approaches based on Kalman filtering have proved their efficacy in tackling the PU problem even when strong discontinuities of the height profile and noisy data are involved. This paper presents a novel multichannel InSAR PU algorithm using several interferometric SAR images based on the extended Kalman filter. The proposed technique exploits the capability of the Kalman algorithm to simultaneously perform noise filtering, PU, and multi-sensor data fusion. The proposed method, even being a Bayesian estimator, optimally fuses height information coming from an additional maximum likelihood estimator (MLE) combining the benefits of both the Bayesian and the non-Bayesian approaches. The performance of the proposed algorithm has been tested on simulated interferometric images proving the effectiveness of the proposed method.

scholarly journals Absolute phase map recovery of two fringe patterns with flexible selection of fringe wavelengths

2014 ◽  
Vol 53 (9) ◽  
pp. 1794 ◽  
Author(s):  
Jiale Long ◽  
Jiangtao Xi ◽  
Ming Zhu ◽  
Wenqing Cheng ◽  
Rui Cheng ◽  
...  
Keyword(s):  
Absolute Phase ◽  
Phase Map ◽  
Fringe Patterns ◽  
Selection Of

scholarly journals High-resolution Three-dimensional Surface Imaging Microscope Based on Digital Fringe Projection Technique

2020 ◽  
Vol 20 (3) ◽  
pp. 139-144
Author(s):  
Cheng-Yang Liu ◽  
Tzu-Ping Yen ◽  
Chien-Wen Chen
Keyword(s):  
High Resolution ◽  
Imaging System ◽  
Three Dimensional ◽  
Fringe Projection ◽  
Surface Imaging ◽  
Projection Technique ◽  
Digital Fringe Projection ◽  
Absolute Phase ◽  
The Absolute ◽  
Fringe Patterns

AbstractThe three-dimensional (3-D) micro-scale surface imaging system based on the digital fringe projection technique for the assessments of microfiber and metric screw is presented in this paper. The proposed system comprises a digital light processing (DLP) projector, a set of optical lenses, a microscope, and a charge coupled device (CCD). The digital seven-step fringe patterns from the DLP projector pass through a set of optical lenses before being focused on the target surface. A set of optical lenses is designed for adjustment and size coupling of fringe patterns. A high-resolution CCD camera is employed to picture these distorted fringe patterns. The wrapped phase map is calculated by seven-step phase-shifting calculation from these distorted fringe patterns. The unwrapping calculation with quality guided path is introduced to compute the absolute phase values. The dimensional calibration methods are used to acquire the transformation between real 3-D shape and the absolute phase value. The capability of complex surface measurement for our system is demonstrated by using ISO standard screw M1.6. The experimental results for microfiber with 3 μm diameter indicate that the spatial and vertical resolutions can reach about 3 μm in our system. The proposed system provides a fast digital imaging system to examine the surface features with high-resolution for automatic optical inspection industry.

scholarly journals Efficient and Accurate Frequency Estimator under Low SNR by Phase Unwrapping

2019 ◽  
Vol 2019 ◽  
pp. 1-6
Author(s):  
Shen Zhou ◽  
Liu Rongfang
Keyword(s):  
Frequency Estimation ◽  
Signal To Noise Ratio ◽  
Additive White Gaussian Noise ◽  
Likelihood Estimation ◽  
Accurate Method ◽  
Phase Unwrapping ◽  
Single Frequency ◽  
Low Snr ◽  
Cramer Rao Bound ◽  
Frequency Estimator

In the case of low signal-to-noise ratio, for the frequency estimation of single-frequency sinusoidal signals with additive white Gaussian noise, the phase unwrapping estimator usually performs poorly. In this paper, an efficient and accurate method is proposed to address this problem. Different from other methods, based on fast Fourier transform, the sampled signals are estimated with the variances approaching the Cramer-Rao bound, followed with the maximum likelihood estimation of the frequency. Experimental results reveal that our estimator has a better performance than other phase unwrapping estimators. Compared with the state-of-the-art method, our estimator has the same accuracy and lower computational complexity. Besides, our estimator does not have the estimation bias.

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